Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific models

Abstract Plant organs consist of multiple cell types that do not operate in isolation, but communicate with each other to maintain proper functions. Here, we extract models specific to three developmental stages of eight root cell types or tissue layers in Arabidopsis thaliana based on a state-of-th...

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Main Authors: Michael Scheunemann, Siobhan M. Brady, Zoran Nikoloski
Format: Article
Language:English
Published: Nature Publishing Group 2018-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-018-26232-8
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spelling doaj-4f609e4ad8c341c894b6025ccf06a70d2020-12-08T05:46:53ZengNature Publishing GroupScientific Reports2045-23222018-05-018111510.1038/s41598-018-26232-8Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific modelsMichael Scheunemann0Siobhan M. Brady1Zoran Nikoloski2Systems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant PhysiologyDepartment of Plant Biology and Genome Center, University of CaliforniaSystems Biology and Mathematical Modeling Group, Max Planck Institute of Molecular Plant PhysiologyAbstract Plant organs consist of multiple cell types that do not operate in isolation, but communicate with each other to maintain proper functions. Here, we extract models specific to three developmental stages of eight root cell types or tissue layers in Arabidopsis thaliana based on a state-of-the-art constraint-based modeling approach with all publicly available transcriptomics and metabolomics data from this system to date. We integrate these models into a multi-cell root model which we investigate with respect to network structure, distribution of fluxes, and concordance to transcriptomics and proteomics data. From a methodological point, we show that the coupling of tissue-specific models in a multi-tissue model yields a higher specificity of the interconnected models with respect to network structure and flux distributions. We use the extracted models to predict and investigate the flux of the growth hormone indole-3-actetate and its antagonist, trans-Zeatin, through the root. While some of predictions are in line with experimental evidence, constraints other than those coming from the metabolic level may be necessary to replicate the flow of indole-3-actetate from other simulation studies. Therefore, our work provides the means for data-driven multi-tissue metabolic model extraction of other Arabidopsis organs in the constraint-based modeling framework.https://doi.org/10.1038/s41598-018-26232-8
collection DOAJ
language English
format Article
sources DOAJ
author Michael Scheunemann
Siobhan M. Brady
Zoran Nikoloski
spellingShingle Michael Scheunemann
Siobhan M. Brady
Zoran Nikoloski
Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific models
Scientific Reports
author_facet Michael Scheunemann
Siobhan M. Brady
Zoran Nikoloski
author_sort Michael Scheunemann
title Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific models
title_short Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific models
title_full Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific models
title_fullStr Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific models
title_full_unstemmed Integration of large-scale data for extraction of integrated Arabidopsis root cell-type specific models
title_sort integration of large-scale data for extraction of integrated arabidopsis root cell-type specific models
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2018-05-01
description Abstract Plant organs consist of multiple cell types that do not operate in isolation, but communicate with each other to maintain proper functions. Here, we extract models specific to three developmental stages of eight root cell types or tissue layers in Arabidopsis thaliana based on a state-of-the-art constraint-based modeling approach with all publicly available transcriptomics and metabolomics data from this system to date. We integrate these models into a multi-cell root model which we investigate with respect to network structure, distribution of fluxes, and concordance to transcriptomics and proteomics data. From a methodological point, we show that the coupling of tissue-specific models in a multi-tissue model yields a higher specificity of the interconnected models with respect to network structure and flux distributions. We use the extracted models to predict and investigate the flux of the growth hormone indole-3-actetate and its antagonist, trans-Zeatin, through the root. While some of predictions are in line with experimental evidence, constraints other than those coming from the metabolic level may be necessary to replicate the flow of indole-3-actetate from other simulation studies. Therefore, our work provides the means for data-driven multi-tissue metabolic model extraction of other Arabidopsis organs in the constraint-based modeling framework.
url https://doi.org/10.1038/s41598-018-26232-8
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